Forecasting NVAT Prices

The Role of Data Science in Agriculture

Orville D. Hombrebueno

December 17, 2024

Hi!

My name is Orville D. Hombrebueno. I am a Math teacher at the College of Teacher Education, Nueva Vizcaya State University.

This talk is about…

  1. Data Science

  2. Data Science in Agriculture

  3. Forecasting Vegetable Prices

  4. SARAI

  5. Challenges

  6. Conclusion

What is Data Science?

Data science is the process of extracting insights from data.

  • Collect data from various sources (weather, soil, satellite images).

  • Clean and prepare the data.

  • Analyze the data to identify patterns and trends.

  • Use the insights to make informed decisions.

Data Science in Agriculture

  • Predictive Analytics: Forecast crop yields, potential problems, and optimal harvest times.

  • Precision Agriculture: Optimize resource usage (water, fertilizer, pesticides) for maximum efficiency.

  • Disease and Pest Detection: Identify and address threats early on.

  • Market Analysis: Analyze market trends to make informed farming decisions.

Forecasting NVAT Prices

Forecasting Monthly Vegetable Prices in the Province of Nueva Vizcaya

by J. N. P. Alap, G. G. Gonzales, E. J. Jimenez, C. D. Pastores,

  1. Describe the monthly prices.
  2. Fit models using automatic algorithms.
  3. Evaluate the performance of these automatic algorithms.
  4. Use the best automatic algorithm to generate forecasts.

Vegetable Prices at NVAT

12 Vegetables:

broccoli, cabbage, carrot, cauliflower, celery, chayote (bunga), cucumber, gabi (galyang), pepper (sultan), pepper (taiwan), potato, wombok

Monthly Prices for Pepper (Taiwan)

Figure 1: Monthly Prices for Pepper (Taiwan)

STL Decomposition

Figure 2: STL Decomposition of Pepper (Taiwan)

Forecast for Pepper (Taiwan)

Figure 3: Forecast for Pepper (Taiwan)

SARAI

Challenges

Here are three challenges identified by Ibrahim (2023) when using data science in agriculture.

  • Lack of understanding.

  • Availability of data.

  • Lack of skills.

Conclusion

  • Data science can improve farming.

  • There are challenges.

  • The future is bright.

Thank you!

Training-Workshop on Convergence of Gender, Livelihood, and Data-Driven Agriculture